6. Why?
● UX is important
● UX sells
● UX is the key differentiator
● People matter
● We aren’t our users
● Build a solution that people want
● Solve a problem people have
9. Qualitative
● Goals
○ Meaning - how people see the world
○ Context - the world in which people act
○ Process - what actions and activities people do
○ Reasoning - why people behave the way they do
● Attributes
○ Creativity - what might be interesting to see?
○ Subjective - influence by personal opinions
○ Inductive reasoning - few examples, then extrapolate
● Data
○ field notes, recordings, diary entries, …
10. Focus Groups & Interviews
● Benefits
○ may be structured, directed, detailed
○ put real people/faces/stories behind data
● Problems
○ highly subjective; open to bias by interviewer
○ not in-situ
● Tools
○ Flow - keep them talking when it’s interesting
○ Non-direction - let them meander
○ Transition - close current; open new conversation
○ Depth - tell me more
11. Design Ethnography
● Comes from anthropology
○ Science!
● In-situ
○ observation, interviews
○ get the real story
● How
○ What people say, do, and use
○ Why they do it this way. Why not another way?
● Be…
○ Non-disruptive, non-interventionist, unbiased
12. Usability Studies
● More appropriate for actual artifacts
○ mock-ups, existing systems, prototypes, etc
● Methods
○ Heuristic Evaluation - rate it against a set of criteria
○ Conceptual Modelling - show & tell
○ Direct Observation - watch people play with it
● Interviews
○ Retrospective - record it then show them
○ Critical Incidence - the parts that stood out
● Data
○ audio/video recordings, handwritten notes
13. Diary Studies
● Participants answer over a period of time
○ Same questions? Different questions? Open/closed?
● Pros
○ Longitudinal, in-depth self-report data
○ Highly detailed; very realistic
○ Trends over time
● Cons
○ Expensive; difficult to get right
○ Self-report data
○ Availability Bias
15. Quantitative
● Goals
○ Numbers
○ Trends in data
○ Read between the lines
○ Answer specific questions
● Attributes
○ Large(r) sample sizes
○ Phone, online, in-person
○ Open vs. closed questions
● Data
○ Means, medians, SDs, regressions, correlations
16. Surveys
● Questionnaires with specific measures,
hypotheses, and results
○ SPECIFIC
● Types of Questions
○ Multiple Choice; Scalar; Matching/Association
○ Open-ended
● Things to consider
○ What to ask? How to ask it?
○ Ordering effects
○ Validity threats
17. Metrics
● Measuring real behavior, interactions, use
○ Doesn’t have to be on a real system
● Numbers!
○ Click-through rates
○ Time spent on an activity
○ Error rate
● Method
○ Have a specific thing to measure
○ Figure out how to measure it
○ Figure out why the results are the way they are
18. Usability Studies
● Not as hard-and-fast as other Qualitative Data
○ In-person, so you can dive deeper
● Be specific (numbers!)
○ Measure success/failure rate
○ Measure time
○ A/B test
● Continuous Evaluation
○ Measure real systems in real use
○ Metrics, analytics, log files
21. Tonight's Meetup
● Socializing/Mingling
● Intros/Announcements
○ Jobs
● Brief Presentation
○ Why research?
○ What research is
○ A few methods
● Workshop!
● Afterparty?